RDF2Graph a tool to recover, understand and validate the ontology of an RDF resource.

Autor: van Dam JC; Laboratory of Systems and Synthetic Biology, Wageningen University, Dreijenplein 10, Wageningen, 6703 HB The Netherlands., Koehorst JJ; Laboratory of Systems and Synthetic Biology, Wageningen University, Dreijenplein 10, Wageningen, 6703 HB The Netherlands., Schaap PJ; Laboratory of Systems and Synthetic Biology, Wageningen University, Dreijenplein 10, Wageningen, 6703 HB The Netherlands., Martins Dos Santos VA; Laboratory of Systems and Synthetic Biology, Wageningen University, Dreijenplein 10, Wageningen, 6703 HB The Netherlands ; LifeGlimmer, GmbH, Markelstrasse 38, Berlin, Germany., Suarez-Diez M; Laboratory of Systems and Synthetic Biology, Wageningen University, Dreijenplein 10, Wageningen, 6703 HB The Netherlands.
Jazyk: angličtina
Zdroj: Journal of biomedical semantics [J Biomed Semantics] 2015 Oct 23; Vol. 6, pp. 39. Date of Electronic Publication: 2015 Oct 23 (Print Publication: 2015).
DOI: 10.1186/s13326-015-0038-9
Abstrakt: Background: Semantic web technologies have a tremendous potential for the integration of heterogeneous data sets. Therefore, an increasing number of widely used biological resources are becoming available in the RDF data model. There are however, no tools available that provide structural overviews of these resources. Such structural overviews are essential to efficiently query these resources and to assess their structural integrity and design, thereby strengthening their use and potential.
Results: Here we present RDF2Graph, a tool that automatically recovers the structure of an RDF resource. The generated overview allows to create complex queries on these resources and to structurally validate newly created resources.
Conclusion: RDF2Graph facilitates the creation of complex queries thereby enabling access to knowledge stored across multiple RDF resources. RDF2Graph facilitates creation of high quality resources and resource descriptions, which in turn increases usability of the semantic web technologies.
Databáze: MEDLINE
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